Welcome. I design and build systems that merge AI architecture, language understanding, and human-centered interaction. My work connects structured reasoning, responsive design, and real-time multimodal analysis—turning data, imagery, and language into cohesive, interactive experiences.

I specialize in API-first architectures built with Next.js, Node.js, and TypeScript, ensuring scalable and observable data flow between services. Deployments often pair Vercel, Neon Postgres, and Drizzle ORM, providing seamless schema versioning, efficient query performance, and well-defined separation between logic and presentation.

I frequently develop distributed systems that coordinate multiple AI agents and models through clear orchestration and structured endpoints.

I build advanced frameworks around large-language-model integration, embedding pipelines, and context-aware orchestration. Proficient with the AI SDK (Anthropic, xAI, and OpenAI), I design streaming chat systems and real-time reasoning layers that support rich, adaptive conversation.

My applications combine:

• Streaming chat interfaces
• Vision-model analysis in TypeScript-based Next.js environments
• Embedding storage & retrieval using OpenAI or Voyage vectors inside Postgres
• RAG-based contextual responses engineered for precision and interpretability

These systems unify multimodal perception and structured reasoning to produce fast, reliable, and deeply informative results.

Using React, Tailwind CSS, and Next.js, I create interfaces that make complex AI behavior legible and intuitive. Many of my front ends support real-time AI streaming, image-driven chat, and dynamic context visualization.

Experienced with Python, pandas, and open-source ETL tooling, I build pipelines supporting semantic search, contextual embeddings, and AI-powered analytics. I favor efficient, open-source solutions, scaling to managed cloud services only when the workload truly warrants it.

Languages & Frameworks TypeScript / JavaScript (ESNext) • Python • SQL (Postgres, Drizzle ORM) • React / Next.js / Tailwind CSS

AI & Data Tooling AI SDK (Anthropic, xAI, OpenAI) • Voyage AI & OpenAI Embeddings • RAG Pipelines • Vision & Multimodal Models • ElevenLabs TTS • Node-based orchestration & streaming

Infra & Deployment Vercel • Neon Postgres • Cloudflare Workers • Docker • WSL • Linux automation

A compact but production-ready system demonstrating:

• Real-time streamed AI chat using the Vercel AI SDK
• Durable conversation storage in Neon Postgres
• Automatic title generation
• Retrieval of past conversations via unique IDs
• Configurable system prompts for adaptable behavior

This project serves as a clean, extensible reference architecture for persistent AI chat applications, and can be used as a foundation for more advanced frameworks such as multi-agent orchestration, RAG-backed conversations, and stateful reasoning pipelines.

🔗 Repo: https://github.com/awselliottai/persistent-chat-by-id

My work centers on clarity, adaptability, and traceability. I build systems that are powerful yet transparent in how they reason—balancing machine precision with human readability.

• Adaptive agent frameworks and orchestration
• Real-time streaming chat and multimodal dialogue
• Context-aware retrieval and RAG optimization
• Generative UIs and TTS-integrated experiences
• Efficient hybrid local/cloud pipelines

If you're interested in AI-driven architecture, multimodal reasoning, or interactive intelligent systems, feel free to reach out or open a discussion.

“Clarity in structure and language leads to clarity in intelligence.”